Predicting CO and NOx emissions from gas turbines: novel data and a benchmark PEMS

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Turkish Journal of Electrical Engineering and Computer Science
Volume:27 Issue:6
Predicting CO and NOx emissions from gas turbines: novel data and a benchmark PEMS

Predicting CO and NOx emissions from gas turbines: novel data and a benchmark PEMS

Authors : Heysem KAYA, Pinar TÜFEKCİ, Erdinç UZUN

Pages : 4783-4796

View : 19 | Download : 8

Publication Date : 0000-00-00

Article Type : Research Paper

Abstract :Predictive emission monitoring systems insert ignore into journalissuearticles values(PEMS); are important tools for validation and backing up of costly continuous emission monitoring systems used in gas-turbine-based power plants. Their implementation relies on the availability of appropriate and ecologically valid data. In this paper, we introduce a novel PEMS dataset collected over five years from a gas turbine for the predictive modeling of the CO and NOx emissions. We analyze the data using a recent machine learning paradigm, and present useful insights about emission predictions. Furthermore, we present a benchmark experimental procedure for comparability of future works on the data
Keywords : Predictive emission monitoring systems, CO, NOx, exhaust emission prediction, gas turbines, extreme learning machine, database

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